Content analysis
2023-04-07
last modified: 2024-03-24
== !
Short description
Content analysis consists in collecting documents and getting insights from them by applying a systematic categorization scheme to them. The results obtained can help the researcher create a model, formulate hypotheses, and develop interpretative narratives about the content discussed in the documents.
Key steps
define a list of categories, in relation to your research question.
These categories are also called "codes", and the list of categories can be called a "coding scheme" or a "coding book".
select which documents to collect. These can be interviews, notes from an ethnography, press articles, social media content… it matters that the type of source and the rules that define which source to be collected, are defined in coherence with the research question.
collect documents (conducting interviews, retrieving articles from a database…)
organize and format documents, as needed. For instance, it will be convenient to transcribe your interviews before you analyze them. Visit the page on free tools to transcribe interviews and any audio file.
you found great documents formatted in pdf? Analyzing the text contained in them might be tricky. To help you with this, I have developped 2 free web tools:
a click & point function to search hundreds of pdfs and return the search terms with their context
a click & point function to extract text from specific regions in hundreds of pdfs.
read the documents and apply your categorization scheme to it: each time you find that a document corresponds to one of your categories, you must write down the exact sentence or paragraph where this happens.
In practice, how do you "write down" the sentence that matches a category?
→ You can simply prepare an Excel spreadsheet where each column is a category
→ each time you find a piece of text in a document that matches a category, paste this text in a new line in the spreadsheet, at the level of the column corresponding to this category.
iterate (modify, improve) on the coding scheme while conducting the analysis, or after it, as necessary.
To go further, read this guide on "The Art of Coding and Thematic Exploration in Qualitative Research" (a reference provided by Dra. Veronica Espinoza)
synthetize results (eg, in a table) and do some simple checks and counts: did all categories of the categorization scheme apply to the content you collected? Do the documents relate to all the categories in the same manner, or are there variations?
Resources for absolute beginners
videos
short and simple academic papers to get more details
You can access the full version of these articles through the library of the school.
Another possibility is to find them through Google Scholar, which identifies free versions for you if they exist.
Stemler, S. (2001). An overview of content analysis. Practical Assessment, Research, and Evaluation, 7(1). link
Zhang, Y. , & Wildemuth, B. M. (2009). Qualitative analysis of content. In B. Wildemuth (Ed.), Applications of Social Research Methods to Questions in Information and Library Science (pp.308-319). Westport, CT: Libraries Unlimited. link
Hsieh, H. F., & Shannon, S. E. (2005). Three Approaches to Qualitative Content Analysis. Qualitative Health Research. link
Tools for content analysis
As described above, content analysis can be performed with simple software:
Microsoft Word to transcribe interviews (if you use interviews!)
A spreadsheet (Excel, Google Sheets…) to organize your coding scheme and the matches you find in the documents.
Many vendors would be happy to sell you more sophisticated solutions, though. You can have a look at:
[Atlas.ti](https://atlasti.com/)
[NVivo](https://lumivero.com/products/nvivo/)
If you have a very good reason to use these software, you can ask the library of your host institution - maybe they have a free license for you?
an example of an academic study using content analysis:
Hindman, L. C., & Walker, N. A. (2020). Sexism in professional sports: How women managers experience and survive sport organizational culture. Journal of Sport Management, 34(1), 64-76. link
To go further
Find other methodology lessons here.
This course is designed by Clement Levallois, and check my free web app for data analysis.